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How Much Will a Data Revolution in Development Cost?

Jerven, Morten LU (2017) In Forum for Development Studies 44(1). p.31-50
Abstract
The UN High Level Panel has called for a data revolution. The world’s population should be counted, measured, weighed, and evaluated. This information should be collected, compiled, aggregated, and presented in such a form that it can usefully inform policy-makers and citizens in aggregated forms, and disaggregated according to region, village, gender, and population group. It is tempting to think that having more and better information will improve policy choices, but this is not automatic. Moreover, demanding more information may lead to a deteriorating supply of information if demand outstrips supply. This article therefore focuses on the cost of the data revolution rather than its possible benefits. The simple starting point is that... (More)
The UN High Level Panel has called for a data revolution. The world’s population should be counted, measured, weighed, and evaluated. This information should be collected, compiled, aggregated, and presented in such a form that it can usefully inform policy-makers and citizens in aggregated forms, and disaggregated according to region, village, gender, and population group. It is tempting to think that having more and better information will improve policy choices, but this is not automatic. Moreover, demanding more information may lead to a deteriorating supply of information if demand outstrips supply. This article therefore focuses on the cost of the data revolution rather than its possible benefits. The simple starting point is that data do have a cost. The cost of the data revolution will be considerable. The costs include the sheer financial cost of monitoring, but importantly extend to include the opportunity cost of competing demands on survey capacity. Particular indicators also influence behavior by skewing activities in favor of completing goals with quantifiable targets. More data are only better data if they contain meaningful information that clearly outweighs the opportunity cost related to its gathering. However, funding available for sustainable development goal (SDG) measurement is limited and there are also institutional capacity limits to be reckoned with. On 11 March 2016, the United Nations Statistical Commission’s Interagency and Expert Group on SDG Indicators (IAEG-SDGs) agreed on 230 individual indicators to monitor the 17 goals and 169 targets. Because the final list of 230 indicators has been a moving target, the research for this article took as the starting point of what a reasonable level of measurement of the millennium development goals would have cost to raise a debate and to give a crude estimate over the cost of the introduction of the SDGs, with their exponential increased demand for data. This is done by bringing together and reconciles the existing information on the costs measurement as a reference for scholars concerned with SDG feasibility and operationalization. (Less)
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author
publishing date
type
Contribution to journal
publication status
published
subject
keywords
sustainable development goals, statistical capacity, population census, poverty survey, United Nations
in
Forum for Development Studies
volume
44
issue
1
pages
20 pages
publisher
Taylor & Francis
external identifiers
  • scopus:85002194823
ISSN
0803-9410
DOI
10.1080/08039410.2016.1260050
language
English
LU publication?
no
id
69cd6d01-8445-404a-8276-01398f9f43fd
date added to LUP
2017-02-22 15:54:34
date last changed
2018-02-18 04:57:23
@article{69cd6d01-8445-404a-8276-01398f9f43fd,
  abstract     = {The UN High Level Panel has called for a data revolution. The world’s population should be counted, measured, weighed, and evaluated. This information should be collected, compiled, aggregated, and presented in such a form that it can usefully inform policy-makers and citizens in aggregated forms, and disaggregated according to region, village, gender, and population group. It is tempting to think that having more and better information will improve policy choices, but this is not automatic. Moreover, demanding more information may lead to a deteriorating supply of information if demand outstrips supply. This article therefore focuses on the cost of the data revolution rather than its possible benefits. The simple starting point is that data do have a cost. The cost of the data revolution will be considerable. The costs include the sheer financial cost of monitoring, but importantly extend to include the opportunity cost of competing demands on survey capacity. Particular indicators also influence behavior by skewing activities in favor of completing goals with quantifiable targets. More data are only better data if they contain meaningful information that clearly outweighs the opportunity cost related to its gathering. However, funding available for sustainable development goal (SDG) measurement is limited and there are also institutional capacity limits to be reckoned with. On 11 March 2016, the United Nations Statistical Commission’s Interagency and Expert Group on SDG Indicators (IAEG-SDGs) agreed on 230 individual indicators to monitor the 17 goals and 169 targets. Because the final list of 230 indicators has been a moving target, the research for this article took as the starting point of what a reasonable level of measurement of the millennium development goals would have cost to raise a debate and to give a crude estimate over the cost of the introduction of the SDGs, with their exponential increased demand for data. This is done by bringing together and reconciles the existing information on the costs measurement as a reference for scholars concerned with SDG feasibility and operationalization.},
  author       = {Jerven, Morten},
  issn         = {0803-9410},
  keyword      = {sustainable development goals,statistical capacity,population census,poverty survey,United Nations},
  language     = {eng},
  month        = {02},
  number       = {1},
  pages        = {31--50},
  publisher    = {Taylor & Francis},
  series       = {Forum for Development Studies},
  title        = {How Much Will a Data Revolution in Development Cost?},
  url          = {http://dx.doi.org/10.1080/08039410.2016.1260050},
  volume       = {44},
  year         = {2017},
}